Wikidata from a Research Perspective--A Systematic Mapping Study of Wikidata

M Farda-Sarbas, C Mueller-Birn - arXiv preprint arXiv:1908.11153, 2019 - arxiv.org
Wikidata is one of the most edited knowledge bases which contains structured data. It serves
as the data source for many projects in the Wikimedia sphere and beyond. Since its …

Recoin: relative completeness in Wikidata

V Balaraman, S Razniewski, W Nutt - … of the The Web Conference 2018, 2018 - dl.acm.org
The collaborative knowledge base Wikidata is the central storage of Wikimedia projects,
containing over 45 million data items. It acts as the hub for interlinking Wikipedia pages …

Overview of the triple scoring task at the wsdm cup 2017

H Bast, B Buchhold, E Haussmann - arXiv preprint arXiv:1712.08081, 2017 - arxiv.org
This paper provides an overview of the triple scoring task at the WSDM Cup 2017, including
a description of the task and the dataset, an overview of the participating teams and their …

Debiasing vandalism detection models at wikidata

S Heindorf, Y Scholten, G Engels… - The World Wide Web …, 2019 - dl.acm.org
Crowdsourced knowledge bases like Wikidata suffer from low-quality edits and vandalism,
employing machine learning-based approaches to detect both kinds of damage. We reveal …

Kronecker decomposition for knowledge graph embeddings

C Demir, J Lienen, AC Ngonga Ngomo - … of the 33rd ACM Conference on …, 2022 - dl.acm.org
Knowledge graph embedding research has mainly focused on learning continuous
representations of entities and relations tailored towards the link prediction problem. Recent …

Attentivechecker: A bi-directional attention flow mechanism for fact verification

S Tokala, G Vishal, A Saha… - Proceedings of the 2019 …, 2019 - aclanthology.org
The recently released FEVER dataset provided benchmark results on a fact-checking task in
which given a factual claim, the system must extract textual evidence (sets of sentences from …

Overview of the wikidata vandalism detection task at wsdm cup 2017

S Heindorf, M Potthast, G Engels, B Stein - arXiv preprint arXiv …, 2017 - arxiv.org
We report on the Wikidata vandalism detection task at the WSDM Cup 2017. The task
received five submissions for which this paper describes their evaluation and a comparison …

Leveraging text and knowledge bases for triple scoring: an ensemble approach-the Bokchoy triple scorer at WSDM Cup 2017

B Ding, Q Wang, B Wang - arXiv preprint arXiv:1712.08356, 2017 - arxiv.org
We present our winning solution for the WSDM Cup 2017 triple scoring task. We devise an
ensemble of four base scorers, so as to leverage the power of both text and knowledge …

Wikidata Vandalism Detection-The Loganberry Vandalism Detector at WSDM Cup 2017

Q Zhu, H Ng, L Liu, Z Ji, B Jiang, J Shen… - arXiv preprint arXiv …, 2017 - arxiv.org
Wikidata is the new, large-scale knowledge base of the Wikimedia Foundation. As it can be
edited by anyone, entries frequently get vandalized, leading to the possibility that it might …

A Production Oriented Approach for Vandalism Detection in Wikidata-The Buffaloberry Vandalism Detector at WSDM Cup 2017

R Crescenzi, M Fernandez, FAG Calabria… - arXiv preprint arXiv …, 2017 - arxiv.org
Wikidata is a free and open knowledge base from the Wikimedia Foundation, that not only
acts as a central storage of structured data for other projects of the organization, but also for …